Question 1 – Simple Linear Regression Dark Scarves is a lead...

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Question 1 – Simple Linear Regression
Dark Scarves is a leading design house and is well known for its haute couture scarves that are made for discerning ladies with deep pocket husbands. Dark has recently embarked on a new distribution strategy by appointing 200 sales agents throughout Malaysia. Miss Bibi, the fashion house founder has collected Sales and Advertising data for all Dark’s agent for the past 6 months and she has appointed you to help her analyze the data (Appendix: Table 1).
Miss Bibi also have a few questions for you to answer:
a) She wonders if agent’s advertising expenditure really helps to increase sales.
b) How much semi-annual sales would an agent make if he/she spends RM500 on advertising.
c) If there is indeed a relationship between sales and advertisement, how much does an agent need to spend on ads to generate RM10,000 in sales.

Question 2 – Multiple Linear Regression
Early in 2008, the Rangkaian Pengangkutan Integrasi Deras Sdn Bhd (Rapid), a company responsible for serving the light rail transit (LRT) needs of a large Eastern city, was faced with rising operating deficits on its system. Also, because of a fiscal austerity program at both the federal and state levels, the hope of receiving additional subsidy support was slim.
The board of directors of Rapid asked the system manager to explore alternatives to alleviate the financial plight of the system. The first suggestion made by the manager was to institute a major cutback in service. This cutback would result in no service after 7:00 P.M., no service on weekends, and a reduced schedule of service during the midday period Monday through Friday.
The board of Rapid indicated that this alternative was not likely to be politically acceptable and could only be considered as a last resort. The board suggested that because it had been over five years since the last basic fare increase, a fare increase from the current level of RM1 to a new level of RM1.50 should be considered. Accordingly, the board ordered the manager to conduct a study of the likely impact of this proposed fare hike.
The system manager has collected data on important variables thought to have a significant impact on the demand for rides on Rapid. These data have been collected over the past 27 years and include the following variables (Appendix: Table 2):
• Price per ride (in cents)
• Population in the metropolitan area serviced by Rapid
• Disposable per capita income
• Parking rate per hour in the downtown area (in cents)
Using the given data, answer the following questions:
a) What is the dependent variable in this demand study?
b) What are the independent variables?
c) What are the expected signs of the variables thought to affect transit ridership on Rapid?
d) Using a multiple regression technique, estimate the coefficients of the demand model for Rapid rides.
e) Interpret the result of the regression model.

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Q1: Since coffecient of advertising is 11.7448 (approx) which shows advertising increases then sales is also increases...

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